CN116206465A - Traffic safety risk early warning system and method based on vehicle-road cooperation - Google Patents
Traffic safety risk early warning system and method based on vehicle-road cooperation Download PDFInfo
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Abstract
The invention discloses a traffic safety risk early warning system and method based on vehicle-road cooperation, wherein the system comprises a sensor, an MCU, an interface buffer circuit, a communication module interface and an identification number setting module; the sensor, the communication module interface and the identification number setting module are connected with the MCU through an interface buffer circuit. The invention can receive the vehicle detection information, complete the tasks of data transmission and summarization among a plurality of local early warning devices, uploading remote fault data, automatically running intelligent early warning strategies, controlling the display of an LED early warning display screen, quickly changing the early warning strategies and the like, and has high integration, performance stability, configuration flexibility and maintenance convenience.
Description
Technical Field
The invention belongs to the field of autonomous early warning of traffic risks, and particularly relates to a traffic safety risk early warning system and method based on vehicle-road cooperation.
Background
At present, the application development of vehicle-road coordination is rapid, the real-time state of road traffic flow is found through road side equipment, the possible traffic risk is predicted and judged in time, and timely information feedback and risk early warning for a vehicle driver are important research and application fields in the current traffic field. The traffic risk early warning system generally comprises three parts, namely a sensor for detecting the traffic flow state of a road, an early warning control unit and an LED display screen. The sensor for detecting the traffic flow state is used for sensing the real-time state of the traffic flow on the road; the early warning control unit is used for receiving the traffic flow state and pre-judging traffic risks according to an early warning algorithm so as to form early warning information; the LED display screen is generally arranged on a road side, and receives and displays the early warning information sent by the early warning controller, so that an early warning target is realized in a picture and text mode.
However, at present, due to the reasons of road traffic environment, installation conditions and the like, the adopted sensors are various, the risk early warning scenes are different, the configuration difference of the traffic early warning system control units is quite large, and great difficulty is brought to equipment configuration and field maintenance, so that the application and popularization of the early warning system are not facilitated. In addition, because the control unit of the early warning system often adopts an industrial personal computer or a fixed programmed embedded controller, the actual system has a series of problems of poor running stability or difficult adjustment of an early warning algorithm and the like.
Disclosure of Invention
Aiming at the problems of poor stability, low intelligent degree, high maintenance cost and the like of the control unit of the conventional early warning system, the invention provides a traffic safety risk early warning system and method based on vehicle-road cooperation, which have the advantages of high integrated stability, flexible configuration and convenient maintenance.
The invention adopts a modularized connection mode, so that the convenience of maintenance and overhaul of the early warning device in the later period can be improved, and the maintenance cost is reduced. The MCU sequentially arranges and gathers the identification number setting modules according to different numbers, continuously monitors the abnormal running track vehicles from point to line, and completes real-time early warning information release by transmitting early warning information to an LED early warning display screen interface according to the abnormal running track conditions of the vehicles.
In order to fully realize the functions of the early warning device, the invention is realized by the following scheme:
traffic safety risk early warning device based on vehicle-road cooperation includes: the system comprises a sensor, an MCU, an interface buffer circuit, a communication module interface and an identification number setting module; the sensor, the communication module interface and the identification number setting module are connected with the MCU through an interface buffer circuit;
the MCU realizes the running track splicing according to the identification number setting module on the running track of the vehicle, and completes the continuity measurement of the running data of the vehicle;
the MCU performs autonomous division of the optimal running speed interval, running scene and risk level on the received sensor data;
the traffic safety risk early warning devices are arranged on different sections, module numbers are set according to the internal identification numbers, and running track continuity detection among the traffic safety risk early warning devices is sequentially carried out on data according to the sequence of the running track of the vehicle;
in the data summarizing and transmitting process, when any traffic safety risk early warning device finds abnormal running speed, the MCU judges whether the received data is correct, and sends early warning information to remind the vehicle of abnormal speed after confirming that the received data is correct, and a continuous detection task is unfolded until the vehicle speed falls into a normal interval.
Further, the MCU comprises a data processing module, a communication module, a fault monitoring module, a data sending module, a data receiving module and a control strategy processing module;
the data processing module is connected with the communication module, and the fault detection module is connected with the data sending/receiving module;
the sensor data is transmitted/spliced among different identification number setting modules through the communication module;
the fault detection module detects faults in the data processing process, records the faults and then sends the faults to the remote control center/cloud; after the remote control center/cloud end judges, the processing result/instruction is fed back to the fault monitoring module;
the data processing module completes mutual transmission of sensor monitoring data acquired among different traffic safety risk early warning devices;
the fault detection module is used for finishing abnormal data of the traffic safety risk early warning device, sending the abnormal data to the master control center/terminal through the data sending module, judging by the terminal, and transmitting a processing result to the fault detection module;
the control strategy processing module senses the change of external environment data in real time through the sensor data and dynamically adjusts the risk level and the optimal running speed interval in real time.
Further, in the control strategy processing module, calculating a rear-end collision risk value in units of decibels; firstly, establishing a tunnel entrance section rear-end collision accident collision model and a kinematic equation, wherein the formula is as follows:
wherein R is indvidual As the rear-end collision risk value of the rear vehicle, P individual To calculate individual collision probability using single vehicle initial state, P base Is a base risk value; calculating the value or distribution function of related variables from unmanned aerial vehicle or driving simulation data, calculating the probability of occurrence of collision and the risk value of driving behavior of a vehicle at the entrance section of a tunnel by using a Monte Carlo simulation method, and dividing the risk level of rear-end collision accidents according to the above method; the rear-end collision probability of the rear-end vehicle is 5/10 6 And early warning is started, and the risk level of the rear-end collision front vehicle of the tunnel entrance section is divided into a plurality of stages according to the 10 multiplying power.
Further, the control strategy processing module is used for changing the braking distance according to different vehicle friction forces under different meteorological conditions, and calculating the optimal running speed by combining the optimal braking distance;
according to a vehicle braking vision range formula:
wherein L is the braking distance, v is the vehicle speed, and f is the vehicle friction.
Further, the arrangement position distance of the early warning device is located at the position 190m in front of the high-risk road section.
Further, the interface buffer circuit is a 74HC245 buffer circuit;
the method comprises the steps of communicating with a 4G wireless communication module, and completing data summarization and uploading of abnormal data by a corresponding communication module interface;
summarizing the number data of the identification number setting modules in the early warning devices arranged on each section, and continuously monitoring the running track from point to face according to the numbers;
the abnormal data receiving task is completed corresponding to the power module interface;
the current is prevented from impacting the diode through the MCU serial port receiving line;
the communication module interface is arranged on the control unit circuit board in a lamination mode.
The invention also relates to a traffic safety risk early warning method based on vehicle-road cooperation, which comprises the following steps:
the sensor transmits the collected vehicle operation data to the MCU through the sensor interface module;
the MCU performs autonomous division of the optimal running speed interval, running scene and risk level on the received sensor data;
the traffic safety risk early warning devices are arranged on different sections, module numbers are set according to the internal identification numbers, and running track continuity detection among the traffic safety risk early warning devices is sequentially carried out on data according to the sequence of the running track of the vehicle;
in the data summarizing and transmitting process, when any traffic safety risk early warning device finds an abnormal running speed, judging whether the received data is correct or not, sending early warning information to remind the vehicle of abnormal speed after confirming that the received data is correct, and unfolding a continuous detection task until the vehicle speed is reduced to a normal interval;
after the MCU receives the digital signals acquired by the sensor, the MCU performs fusion judgment on the vehicle type data and the sensor data after finishing data analysis, and divides the optimal running vehicle speed interval and the risk level.
Further, detecting faults in the data processing process, recording the faults, and then sending the faults to a remote control center/cloud by a data sending module; after the remote control center/cloud end judges, the processing result/instruction is fed back;
transmitting sensor monitoring data acquired among different traffic safety risk early warning devices;
the method comprises the steps of finishing abnormal data of a traffic safety risk early warning device, sending the abnormal data to a main control center/terminal through a data sending module, judging by the terminal, and transmitting a processing result;
and sensing the change of external environment data in real time through the sensor data, and dynamically adjusting the risk level and the optimal running speed interval in real time.
Further, calculating a rear-end collision risk value in decibels; firstly, establishing a tunnel entrance section rear-end collision accident collision model and a kinematic equation, wherein the formula is as follows:
wherein R is individual As the rear-end collision risk value of the rear vehicle, P individual To calculate individual collision probability using single vehicle initial state, P base Is a base risk value; calculating the value or distribution function of related variables from unmanned aerial vehicle or driving simulation data, calculating the probability of occurrence of collision and the risk value of driving behavior of a vehicle at the entrance section of a tunnel by using a Monte Carlo simulation method, and dividing the risk level of rear-end collision accidents according to the above method; the rear-end collision probability of the rear-end vehicle is 5/10 6 And early warning is started, and the risk level of the rear-end collision front vehicle of the tunnel entrance section is divided into a plurality of stages according to the 10 multiplying power.
Further, according to different friction forces of the vehicle under different meteorological conditions, the braking distance is changed, and the optimal running speed is calculated by combining the optimal braking distance;
according to a vehicle braking vision range formula:
wherein L is the braking distance, v is the vehicle speed, and f is the vehicle friction.
The invention adopts the interface buffer circuit design, protects the core control circuit to a great extent, and avoids the damage to the post-stage circuit caused by the damage of any module.
The interface buffer circuit adopts a tri-state gate buffer chip, has a wide voltage range and stronger fan-out capability, and can avoid direct connection between the MCU and external equipment and high-power equipment when connecting other modules and external interfaces, thereby effectively improving the safety and stability of the system; meanwhile, all interfaces of the buffer are provided with LED display lamps, so that the detection and maintenance are convenient. The damage of instantaneous spike voltage and current to the subsequent circuit caused by on-off instant is prevented; the function of the series resistor is mainly to prevent echo.
The data receiving module, the data processing module, the communication module, the fault monitoring module, the data transmitting module and the data receiving module adopt modularized circuit designs, adopt a plurality of isolation modes, and independently operate among the modules, so that crosstalk among the modules of the circuit is avoided.
The MCU can complete vehicle running data and sensor data processing through the sensors connected with the sensor module interface, and complete optimal running speed division aiming at the acquired data.
The MCU can collect vehicle information and sensor data collected by the identification number setting modules in the early warning devices arranged on different sections, and the early warning information release is finished by transmitting the early warning information to the LED early warning display screen interface according to the divided optimal running speed and the identification number setting modules with different numbers according to the serial monitoring of the running track of the vehicle from point to line in sequence and aiming at the abnormal situation of the running track of the vehicle. The MCU senses the change of external environment data such as weather and the like in real time through the sensor data, and dynamically adjusts the risk level and the optimal running speed interval in real time.
And if the abnormal value of the abnormal data in the detection of different modules on the hardware circuit board is larger than the specified variable in the initial function, triggering an interrupt function in the core control MCU to send the abnormal data received by the core control MCU to the master control center through the 4G module for decision making and fault diagnosis.
Drawings
FIG. 1 is a system block diagram of an embodiment of the present invention;
FIG. 2 is a schematic diagram of an MCU peripheral circuit according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an interface buffer circuit according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an interface circuit according to an embodiment of the present invention;
fig. 5 is a flowchart illustrating an operation of the active vehicle-road collaborative risk early warning controller according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. Based on the embodiments, all other embodiments that may be made by one of ordinary skill in the art without making any inventive effort are within the scope of the present application.
Unless otherwise defined, technical or scientific terms used in the embodiments of the present application should be given a general meaning as understood by one of ordinary skill in the art. The terms "first," "second," and the like, as used in this embodiment, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items. "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. "upper", "lower", "left", "right", "transverse", and "vertical", etc. are used only with respect to the orientation of the components in the drawings, these directional terms are relative terms, which are used for descriptive and clarity with respect thereto and which may vary accordingly with respect to the orientation in which the components are disposed in the drawings.
Example 1
The traffic safety risk early warning device based on vehicle-road cooperation in this embodiment, as shown in fig. 1, includes a sensor, a sensor module interface, an MCU, an interface buffer circuit, a communication module interface, a power module interface, an LED early warning display screen interface, an identification number setting module, an expansion RAM module and an SD card module.
The MCU realizes the running track splicing according to the identification number setting module on the running track of the vehicle, and the continuity measurement of the running data of the vehicle is completed.
The sensor is connected with the MCU and the power module through the sensor module interface.
The MCU is connected with the interface buffer circuit, the power module interface, the communication module interface, the expansion RAM module and the SD card module. The communication module interface is connected with the power module interface.
The sensor module interface-adapted sensor comprises one or more of a fog concentration monitor, a millimeter wave radar, a rainfall sensor, a water film thickness detector and a hub temperature detector.
The power module interface can complete wide voltage input and multipath voltage output.
The wireless communication module can be matched with one or more of LORA, bluetooth, wiFi, zigBee and 4G modules.
The communication module interface, the sensor module interface, the LED display screen control module interface and the identification number setting module are respectively connected with the interface buffer circuit, and the interface buffer circuit is connected with the MCU.
The expansion RAM module and the SD card module are directly connected with the MCU.
The MCU comprises a data processing module, a communication module, a fault monitoring module, a data sending module, a data receiving module and a control strategy processing module.
The data processing module is connected with the communication module, and the fault detection module is connected with the data sending/receiving module.
The data processing module is used for completing mutual transmission of sensor monitoring data acquired among different traffic safety risk early warning devices. And the data transmission and the vehicle running track data splicing work are conveniently completed.
The fault detection module is used for finishing abnormal data of the traffic safety risk early warning device, sending the abnormal data to the master control center/terminal through the data sending module, judging by the terminal, and transmitting a processing result to the fault detection module.
After sensor data are transmitted into the MCU and converted from analog quantity to digital quantity, the sensor data are transmitted to the MCU through a communication module (serial port) in the MCU, so that data transmission/splicing among different identification number setting modules is completed.
The fault detection module is responsible for detecting faults (data loss/messy codes) in the data processing process, records the faults and then sends the faults to the remote control center/cloud end through the data sending module. And after the remote control center/cloud end judges, the processing result/instruction is fed back to the fault monitoring module.
The control strategy processing module can sense the change of external environment data such as weather and the like in real time through the sensor data, and dynamically adjust the risk level and the optimal running speed interval in real time.
The control strategy processing module senses and dynamically adjusts the external environment data such as weather and the like acquired by the sensor in real time. According to a vehicle braking vision range formula:
wherein L is the braking distance, and v is the vehicle speed. The braking distance varies according to the friction of the vehicle under different meteorological conditions. Therefore, the control strategy can calculate the optimal running speed according to the friction force under different meteorological conditions and combining the optimal braking distance.
After the MCU receives the digital signals acquired by the sensor, the control strategy module performs fusion judgment on the vehicle type data and the sensor data after the MCU finishes data analysis, and divides the optimal running speed interval and the risk level.
The identification number setting module uses coded switch control. The expansion RAM module is connected with the serial random access memory by adopting a high-speed synchronous serial port. The SD card module is connected with the communication module interface by adopting a high-speed synchronous serial port.
The sensor is matched with various multi-path data output modes and transmits the acquired data to the MCU. The power module can real-time detect the temperatures of different modules on the hardware circuit board and transmit abnormal data to the MCU.
As shown in fig. 2, in this embodiment, the MCU uses a 32-bit single-chip microcomputer from the company of semiconductor, and has a 48KB on-chip SRAM, a 256KB on-chip program storage FLAS,12 DMA channels, 3 SPI (high speed synchronization serial ports), 5 serial communication ports, and 64 general IO ports.
In this embodiment, the MCU is connected to the control unit through the socket, and may use 8 pins of two SPI ports to connect the expansion RAM module and the SD card module, use 10 pins of 5 serial ports to connect the communication module interface, the LED early warning display screen interface, the power module interface, and use 4 general IO pins to connect the identification number setting module.
As shown in fig. 3 and 4, in the active vehicle-road collaborative risk early warning device in this embodiment:
interface buffer circuit 74HC245 buffer circuit includes diode, tri-state gate buffer chip, current limiting resistor. The serial ports 2, 4, 5 binding posts of serial ports all adopt 5V voltage to carry out external power supply for the system, and 12V voltage can outwards supply power, and binding posts reserve redundant interface and make things convenient for the sensor quantity of connecting of later stage expansion. The interface buffer circuit adopts a tri-state gate buffer chip, has a wide voltage range and stronger fan-out capability, and can avoid direct connection between the MCU and external equipment and high-power equipment when connecting other modules and external interfaces, thereby effectively improving the safety and stability of the system; meanwhile, all interfaces of the buffer are provided with LED display lamps, so that the detection and maintenance are convenient. The damage of instantaneous spike voltage and current to the subsequent circuit caused by on-off instant is prevented; the current limiting resistor is used to prevent echo. Wherein:
and (3) a step of: the data output serial port No. 1 is U1 Tx, the data input serial port No. 1U 1 Rx is connected with the first serial port of the MCU, and the data is communicated with the 4G wireless communication module in the communication module interface through the data output pin 1_TxD through the 74HC245 buffer circuit, so that the uploading task of abnormal data is completed.
And II: the data output serial port No. 2 is connected with the MCU second serial port, the serial port is connected with the MCU second serial port through the 74HC245 buffer circuit, the serial number data of the identification number setting module in the early warning device arranged on each section are summarized through the data output pin 2_TxD, and the continuous monitoring of the running track from point to face is carried out according to the serial number.
Thirdly,: the data output serial port No. 3 is connected with the MCU third serial port, and the data summarization is completed through the 74HC245 buffer circuit, the data output pin 3 433_TxD and the data input pin 3 433_RxD corresponding to the communication module interface.
Fourth, the method comprises the following steps: the data output serial port No. 5 is connected with the MCU fifth serial port, the data input serial port No. 5 passes through the 74HC245 buffer circuit, and the abnormal data receiving task is completed through the data output pin 5_TxD and the data input pin 5_RxD corresponding to the power module interface.
Fifth step: diodes VD1, VD2, VD3, VD4, VD5 are MCU serial port receiving lines to prevent current from striking the diodes.
Sixth,: the light emitting diodes D1, D1t, D2t, D3t, D4t, D5 and D5t are serial communication uplink and downlink indicator lamps with five serial ports respectively.
Seventh,: 4R1, 4R2, 4R3, 4R4 are pull-up and current limiting resistors, respectively, and R1 is a pull-up resistor.
Eighth step: the communication module interface directly adopts an ATK-LORA-01 integrated LoRa module and is arranged on a control unit circuit board in a lamination mode.
Nine: the 4G remote communication module directly adopts a general CAT1 integrated module and is arranged on a control unit circuit board.
As shown in fig. 5, the early warning method of the present embodiment is performed as follows:
and after the power supply supplies power for the system normally, the system performs initialization self-checking operation.
The sensor transmits the collected vehicle operation data to the MCU through the sensor interface module.
And the MCU autonomously divides the received sensor data into an optimal running speed interval, a running scene and a risk level.
And the traffic safety risk early warning devices with different section arrangements are used for sequentially carrying out data summarization transmission (continuous detection of running track) among the traffic safety risk early warning devices according to the sequence of the running track of the vehicle by setting module numbers according to the internal identification numbers.
In the data summarizing and transmitting process, when any traffic safety risk early warning device finds that the data is abnormal in monitoring (abnormal running speed), whether the received data is correct or not is autonomously judged, early warning information is sent to remind that the vehicle speed is abnormal after the received data is confirmed to be correct, and a continuous detection task is unfolded until the vehicle speed is reduced to be in a normal interval.
After the MCU receives the digital signals acquired by the sensor, the MCU internal control strategy performs fusion judgment on the vehicle type data and the sensor data after the MCU finishes data analysis, and divides the optimal running speed interval and the risk level.
The MCU calculates the rear-end collision risk value in decibels. Firstly, a tunnel entrance section rear-end collision accident model and a kinematic equation are established, and the following formula is shown:
wherein R is individual As the rear-end collision risk value of the rear vehicle, P individual To calculate individual collision probability using single vehicle initial state, P base Is the base risk value. And calculating the value or distribution function of the related variable from the unmanned plane or driving simulation data, calculating the probability of occurrence of the collision and the driving behavior risk value of the vehicle at the entrance section of the tunnel by using a Monte Carlo simulation method, and dividing the rear-end collision accident risk level according to the above. The rear-end collision probability of the rear-end vehicle is 5/10 6 Early warning is started, the risk level of rear-end collision of the rear vehicle and the front vehicle of the tunnel entrance road section is divided into four stages according to 10 multiplying power, the risk level is lower (I), the risk level is low (II), the risk level is medium (III) and the risk level is high (IV).
As shown in table 1, the continuity of the abnormal running track vehicles is monitored, the running track of the abnormal running track vehicles is sequentially summarized and monitored in real time according to the serial numbers of the identification number setting modules in the early warning devices arranged on different sections, and early warning information is dynamically issued in real time according to the decision result of the early warning devices.
TABLE 1 optimal vehicle speed and risk classification
| Small-sized vehicle speed (km/h) | Large vehicle speed (km/h) | Risk level |
| (80，90] | (60，70] | I |
| (90，100] | (70，80] | II |
| (100，110] | (80，90] | III |
| ＞110 | ＞100 | IV |
And for abnormal data appearing in the detection of different modules on the hardware circuit board, if the abnormal value is larger than a specified variable in the initial function, triggering an interrupt function in the MCU to send the abnormal data to the master control center through the 4G module.
When the four power supply pins on the MCU have no voltage or abnormal data reading (messy codes and no data output), the serial numbers of the sensors connected with the module are stored and recorded, and the data are sent to the master control center/terminal.
The minimum distance between the arrangement position of the early warning device and the starting point of the high-risk road section can meet the safety deceleration distance of different vehicle types, and the formula can be obtained:
in the formula (1), V 0 The dividing speed value is 95%, the trolley value is 110km/h, and the cart value is 85km/h; v (V) Powder (D) The speed limit value of the high-risk road section is 80km/h, and the value of the cart is 60km/h; a is 15% of the fractional speed limit value, and the trolley takes the value of-2 m/s 2 Taking-4 m/s from cart 2 . Therefore, the position distance of the early warning device is calculated to be 190m in front of the high-risk road section after substituting the data.
As shown in fig. 2 and 4, the vehicle detector interface, the power control interface and the LED early warning display screen interface respectively adopt two power supply mode connectors, so as to adapt to three power supply modes of 12V, 5V and 3.3V and meet different power supply requirements of different sensors and devices on site.
The embodiment adopts the design of an interface buffer circuit, so that the core control circuit is protected to a great extent, and the damage to a later-stage circuit caused by the damage of any module is avoided.
The data receiving module, the data processing module, the communication module, the fault monitoring module, the data transmitting module and the data receiving module of the core control MCU of the embodiment adopt modularized circuit designs, adopt various isolation modes, run independently of each other, and avoid crosstalk among all modules of the circuit.
The MCU can complete vehicle running data and sensor data processing through a sensor connected with the sensor module interface, and complete optimal running speed division aiming at the acquired data.
The MCU can collect vehicle information and sensor data collected by the identification number setting modules in the early warning devices arranged on different sections, and the early warning information release is finished by transmitting the early warning information to the LED early warning display screen interface under the condition that the vehicle running track is abnormal according to the number and the continuity monitoring of the vehicle running track sequentially from point to line by the identification number setting modules with different numbers according to the divided optimal running speed.
The data processing module in the MCU can sense the change of external environment data such as weather and the like in real time through the sensor data, and dynamically adjust the risk level and the optimal running speed interval in real time.
If the abnormal value is larger than the specified variable in the initial function, triggering an interrupt function in the MCU, and transmitting the abnormal data received by the MCU to a general control center through the 4G module.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (10)
1. Traffic safety risk early warning device based on car road cooperation, characterized by comprising: the system comprises a sensor, an MCU, an interface buffer circuit, a communication module interface and an identification number setting module; the sensor, the communication module interface and the identification number setting module are connected with the MCU through an interface buffer circuit;
the MCU realizes the running track splicing according to the identification number setting module on the running track of the vehicle, and completes the continuity measurement of the running data of the vehicle;
the MCU performs autonomous division of the optimal running speed interval, running scene and risk level on the received sensor data;
the traffic safety risk early warning devices are arranged on different sections, module numbers are set according to the internal identification numbers, and running track continuity detection among the traffic safety risk early warning devices is sequentially carried out on data according to the sequence of the running track of the vehicle;
in the data summarizing and transmitting process, when any traffic safety risk early warning device finds abnormal running speed, the MCU judges whether the received data is correct, and sends early warning information to remind the vehicle of abnormal speed after confirming that the received data is correct, and a continuous detection task is unfolded until the vehicle speed falls into a normal interval.
2. The apparatus according to claim 1, wherein: the MCU comprises a data processing module, a communication module, a fault monitoring module, a data sending module, a data receiving module and a control strategy processing module;
the data processing module is connected with the communication module, and the fault detection module is connected with the data sending/receiving module;
the sensor data is transmitted/spliced among different identification number setting modules through the communication module;
the fault detection module detects faults in the data processing process, records the faults and then sends the faults to the remote control center/cloud; after the remote control center/cloud end judges, the processing result/instruction is fed back to the fault monitoring module;
the data processing module completes mutual transmission of sensor monitoring data acquired among different traffic safety risk early warning devices;
the fault detection module is used for finishing abnormal data of the traffic safety risk early warning device, sending the abnormal data to the master control center/terminal through the data sending module, judging by the terminal, and transmitting a processing result to the fault detection module;
the control strategy processing module senses the change of external environment data in real time through the sensor data and dynamically adjusts the risk level and the optimal running speed interval in real time.
3. The apparatus according to claim 2, wherein: in the control strategy processing module, calculating a rear-end collision risk value in a decibel unit; firstly, establishing a tunnel entrance section rear-end collision accident collision model and a kinematic equation, wherein the formula is as follows:
wherein R is individual As the rear-end collision risk value of the rear vehicle, P individual To calculate individual collision probability using single vehicle initial state, P base Is a base risk value; the value or the distribution function of the related variable is counted from unmanned plane or driving simulation data, the Monte Carlo simulation method is used for calculating the probability of occurrence of the collision of the vehicle at the entrance section of the tunnel and the driving behavior risk value,dividing the risk level of the rear-end collision accident according to the above type; the rear-end collision probability of the rear-end vehicle is 5/10 6 And early warning is started, and the risk level of the rear-end collision front vehicle of the tunnel entrance section is divided into a plurality of stages according to the 10 multiplying power.
4. The apparatus according to claim 2, wherein: the control strategy processing module is used for changing the braking distance according to different vehicle friction forces under different meteorological conditions, and calculating the optimal running speed by combining the optimal braking distance;
according to a vehicle braking vision range formula:
wherein L is the braking distance, v is the vehicle speed, and f is the vehicle friction.
5. The apparatus according to claim 1, wherein: the arrangement position distance of the early warning device is located at the position 190m in front of the high-risk road section.
6. The apparatus according to claim 1, wherein: the interface buffer circuit is a 74HC245 buffer circuit;
the method comprises the steps of communicating with a 4G wireless communication module, and completing data summarization and uploading of abnormal data by a corresponding communication module interface;
summarizing the number data of the identification number setting modules in the early warning devices arranged on each section, and continuously monitoring the running track from point to face according to the numbers;
the abnormal data receiving task is completed corresponding to the power module interface;
the current is prevented from impacting the diode through the MCU serial port receiving line;
the communication module interface is arranged on the control unit circuit board in a lamination mode.
7. A traffic safety risk early warning method based on vehicle-road cooperation is characterized in that: the method comprises the following steps:
the sensor transmits the collected vehicle operation data to the MCU through the sensor interface module;
the MCU performs autonomous division of the optimal running speed interval, running scene and risk level on the received sensor data;
the traffic safety risk early warning devices are arranged on different sections, module numbers are set according to the internal identification numbers, and running track continuity detection among the traffic safety risk early warning devices is sequentially carried out on data according to the sequence of the running track of the vehicle;
in the data summarizing and transmitting process, when any traffic safety risk early warning device finds an abnormal running speed, judging whether the received data is correct or not, sending early warning information to remind the vehicle of abnormal speed after confirming that the received data is correct, and unfolding a continuous detection task until the vehicle speed is reduced to a normal interval;
after the MCU receives the digital signals acquired by the sensor, the MCU performs fusion judgment on the vehicle type data and the sensor data after finishing data analysis, and divides the optimal running vehicle speed interval and the risk level.
8. The method according to claim 7, wherein:
detecting faults in the data processing process, recording the faults, and transmitting the faults to a remote control center/cloud by a data transmitting module; after the remote control center/cloud end judges, the processing result/instruction is fed back;
transmitting sensor monitoring data acquired among different traffic safety risk early warning devices;
the method comprises the steps of finishing abnormal data of a traffic safety risk early warning device, sending the abnormal data to a main control center/terminal through a data sending module, judging by the terminal, and transmitting a processing result;
and sensing the change of external environment data in real time through the sensor data, and dynamically adjusting the risk level and the optimal running speed interval in real time.
9. The method according to claim 8, wherein: calculating a rear-end collision risk value in decibels; firstly, establishing a tunnel entrance section rear-end collision accident collision model and a kinematic equation, wherein the formula is as follows:
wherein R is individual As the rear-end collision risk value of the rear vehicle, P individual To calculate individual collision probability using single vehicle initial state, P base Is a base risk value; calculating the value or distribution function of related variables from unmanned aerial vehicle or driving simulation data, calculating the probability of occurrence of collision and the risk value of driving behavior of a vehicle at the entrance section of a tunnel by using a Monte Carlo simulation method, and dividing the risk level of rear-end collision accidents according to the above method; the rear-end collision probability of the rear-end vehicle is 5/10 6 And early warning is started, and the risk level of the rear-end collision front vehicle of the tunnel entrance section is divided into a plurality of stages according to the 10 multiplying power.
10. The method according to claim 8, wherein: according to different friction forces of the vehicle under different meteorological conditions, the braking distance is changed, and the optimal running speed is calculated by combining the optimal braking distance;
according to a vehicle braking vision range formula:
wherein L is the braking distance, v is the vehicle speed, and f is the vehicle friction.
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